February 1, 2023

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The Industry was Quick to Embrace Viewability

Viewability as a standard measurement metric for digital advertising emerged out of necessity around 2010, in response to a “wild West” market landscape of proliferating exchanges, publishers and tech platforms. With little top-down oversight, the open advertising environment was rife with fraud and unfulfilled promises. Brands and agencies alike were quick to realize their vulnerability when it came to proving the value and authenticity of paid-for ad impressions.

At the time, an array of imperfect technology and bad actors directed many automated placements to undesirable or low-quality sites (like pornography or clickbait), with formats that were often entirely without value because they appeared under or beneath other content. The array of problematic inefficiencies ran the full spectrum from simple oversight to outright fraud, but the inevitable conclusion remained: Something had to be done.

The answer for the moment was viewability – a measure of hygiene that ensured that ad impressions conveyed at least potential value by at least being literally visible on-screen. Since then, however, circumstances have changed dramatically, and new approaches are emerging to measurement and optimization that promise similar gains in efficiency. One of the most promising new technologies is attention measurement, but many questions remain: How does one measure attention? Where is it properly applied to digital campaigns? And, finally, how is attention measurement different from viewability?

The Media Research Council decided in 2012 that in order to be considered “viewable,” 50% of the ad creative had to be visible for at least one second in the viewable space of the browser (the standards have been updated somewhat since then). Problem solved, or so it seemed. As a much more robust metric than simple impressions, the wide-scale adoption of viewability enabled great efficiencies across the ecosystem.

Much has changed since then, and continues to change still. Evolving data privacy standards and new technologies have meant that advertisers can’t target and measure campaigns as they have grown accustomed to, and the shortcomings of viewability itself have become apparent (viewability still can’t show if an impression was actually viewed vs. merely in-view). Viewability also risks prompting a broad-scale reduction in inventory quality and viewer experience, with pages overloaded with formats designed by algorithm to maximize viewability returns.

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Enter attention measurement.

Studies have shown that attention can be orders of magnitude more accurate at predicting campaign results than viewability. Attention is also evolving to be applied across newer channels and formats. Attention is getting better all the time as a tool for measuring CTV, social channels and even in-game advertising.

Attention hasn’t achieved sufficiently wide adoption, however, to inspire the same rapid uptake that led the MRC to quickly define and standardize viewability. This is likely because advertisers are wary of too quickly adopting new methods when operations were otherwise proceeding smoothly.

A growing number of players in the ecosystem are looking closely at attention metrics as a new currency for ad measurement, but the lack of a standard definition is proving an obstacle. Some approaches to attention use proxies or probabilistic modeling without any other verification. Other solutions use eye-tracking or facial coding to build their technology.

Agencies and brands are paying attention, and many are currently deciding between different approaches to attention measurement in building their own solutions. According to the ARF, 94% of media buyers expect that attention metrics will strengthen and augment current solutions. A standardized approach could help, but there are likely too many practical variables when it comes to attention measurement. Instead, advertisers should look to explore and test the solutions that support their desired strategies – display, video, audio, pre-planning, real-time optimisation, bespoke studies, or other needs. With this, the industry can work toward a more promising, efficient future that brings fundamental value to all players in the ecosystem.

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